Understanding the risk of arrhythmias, such as those that may stem from pharmaceuticals and cardiac pathologies, can be important in order to apply desirable and cost-effective therapeutic approaches and treat diseases based upon patient-specific medical conditions and risks for developing a dangerous arrhythmia. For instance, understanding such risk can be helpful for patients diagnosed with cardiac diseases including heart failure and myocardial ischemia. The risk of arrhythmias is often assessed in both preclinical and clinical studies. For instance, the proarrhythmic risk of medications is often assessed in preclinical studies using several approaches. Clinical studies involving the QT interval of a cardiac cycle, such as those involving measurement of QT prolongation on healthy human subjects, can also be performed to assess the proarrhythmic risk of new medications.
However, such studies and assessments have been challenging to implement. It is often desirable to perform these assessments on ambulating human and animal subjects. However, performing these assessments on ambulatory subjects is difficult or impractical because either the required measurements are highly invasive or because the signals acquired using minimally invasive or non-invasive sensing techniques often result in signals that are sufficiently noisy and for which consistently accurate measurements are not possible. As evidence of these challenges, a significant percentage of pharmaceuticals that show no indication of proarrhythmic risk in preclinical studies eventually demonstrate evidence of proarrhythmic risk later in either development or post marketing. In addition, commonly used risk indicators are heart rate dependent and can hence be difficult to interpret. One of the unfortunate consequences of the lack of a reliable and sensitive cardiac risk metric is that preclinical studies sometimes falsely eliminate safe and effective drugs from the development pipeline based on metrics that have low predictive accuracy.
Techniques used to assess proarrhythmic risk in clinical care have also been challenging to implement in accurately assessing the risk of cardiac arrhythmias, such as for patients that have experienced myocardial infarction and those diagnosed with systolic heart failure and coronary artery disease. Unfortunately, the vast majority of deaths caused by dangerous arrhythmias occur in populations where existing techniques have proven ineffective and no practical and cost-effective options exist to accurately assess arrhythmic risk in these populations. Further, analyzing characteristics on ambulatory patients can be difficult. These and other characteristics have been challenging to the characterization of cardiac function, and risk associated therewith.